An Emergency Evacuation Model Based on Computer Vision Smart Inducing in Hotel Stampede Environment

2014 ◽  
Vol 556-562 ◽  
pp. 5736-5739 ◽  
Author(s):  
Kun Gao
Keyword(s):  
Computer Vision ◽  
Flow Direction ◽  
Local Area ◽  
Emergency Evacuation ◽  
Flow Density ◽  
Strong Nonlinearity ◽  
Flow Information ◽  
Direction Of Movement ◽  
Control Terminal ◽  
Rapid Evacuation

Stampede accidents in hotel crowded area will cause disorder in flow information. As we know, flow density and direction of movement have strong nonlinearity and mutation. This paper proposes a complex network model for rapid evacuation based on computer vision smart inducing. On basis of images' process, the paper fully considers the mutation of flow and direction by the mutation operator of flow direction, and increases the evacuation speed by extracting mutation parameter of local area and feeding back it to control terminal. The experiment results show that the proposed algorithm improves the accuracy and speed of evacuation in hotel stampede environment.

Optimization Mechanism Modeling for Emergency Evacuation in Group Incidents

2014 ◽  
Vol 513-517 ◽  
pp. 3224-3227
Author(s):  
Yu Jie Liu
Keyword(s):  
Model Simulation ◽  
Emergency Evacuation ◽  
Collision Probability ◽  
Flow Density ◽  
Route Guidance ◽  
Estimation Model ◽  
Motion Direction ◽  
Smooth Flow ◽  
Flow Information ◽  
Evacuation Route

The paper mainly discusses the emergency evacuation when group incident occurs. In crowded areas, group incidents will result in disorder of flow information, nonlinear and catastrophe of flow density and motion direction. The traditional evacuation route guidance only selects evacuation route for orderly, smooth flow density variations, in which nonlinearity and mutation of the flow information cannot be reflected. Therefore, once the Group incidents occurred, the stability of the model will be destroyed. To solve the problem, the paper proposes an emergency evacuation method based on path collision probability estimation model. Simulation results show that this algorithm can improve the speed of evacuation.

scholarly journals Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases

2020 ◽  
Vol 17 (17) ◽  
pp. 6359 ◽  
Author(s):  
Quynh C. Nguyen ◽  
Yuru Huang ◽  
Abhinav Kumar ◽  
Haoshu Duan ◽  
Jessica M. Keralis ◽  
...  
Keyword(s):  
Computer Vision ◽  
Built Environment ◽  
Local Area ◽  
Physical Disorder ◽  
Single Family ◽  
Google Street View ◽  
Environment Effects ◽  
Street View ◽  
Sociodemographic Disparities ◽  
Family Home

The spread of COVID-19 is not evenly distributed. Neighborhood environments may structure risks and resources that produce COVID-19 disparities. Neighborhood built environments that allow greater flow of people into an area or impede social distancing practices may increase residents’ risk for contracting the virus. We leveraged Google Street View (GSV) images and computer vision to detect built environment features (presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires). We utilized Poisson regression models to determine associations of built environment characteristics with COVID-19 cases. Indicators of mixed land use (non-single family home), walkability (sidewalks), and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were connected with fewer COVID-19 cases. Percent black and percent with less than a high school education were associated with more COVID-19 cases. Our findings suggest that built environment characteristics can help characterize community-level COVID-19 risk. Sociodemographic disparities also highlight differential COVID-19 risk across groups of people. Computer vision and big data image sources make national studies of built environment effects on COVID-19 risk possible, to inform local area decision-making.

scholarly journals Application of Extended Lattice Gas Automata Model in Ship Evacuation Simulation

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Haoyang Han ◽  
Jundong Zhang ◽  
Ruizheng Jiang
Keyword(s):  
Lattice Gas ◽  
Emergency Evacuation ◽  
Flow Density ◽  
Extended Model ◽  
Movement Behaviour ◽  
Evacuation Simulation ◽  
Lattice Gas Automata ◽  
Research Article ◽  
Proposed Model ◽  
Test Scenarios

Lattice gas automaton is a mathematical model that is used to simulate the horizontal uniform evacuation behaviour of a group. However, extended lattice gas automata model is proposed to examine marine evacuation behaviour, which is subject to deck heeling. The application of distance accumulation algorithm and the conversion probability mostly make the extended model, while the approach deals with the most complicated ship evacuation. Moreover, the suggested model is expected to enhance the safety and efficiency of evacuation. The distance accumulation lattice gas automata model considers multiple movement behaviours, flow density, deck heeling, counterflow, and congestion. Movement behaviour will be severely affected in deck heeling process where people may walk normally, walk while bent over, or crawl. To verify the proposed model, 11 test scenarios and several emergency evacuation scenarios are demonstrated. The simulation results explain the validity of another experimental model. The number of people in counterflow, deck heeling, and difference in movement have a direct effect on evacuation, which is as discussed in results. This research article provides a brief study on ship design and crew response behaviour in case of mishap/accident.

Research to Household Sub-Network Development Based on Bluetooth Control Technology

2014 ◽  
Vol 989-994 ◽  
pp. 4215-4218
Author(s):  
Long Qian
Keyword(s):  
Ad Hoc ◽  
Local Area Network ◽  
Local Area ◽  
Home Network ◽  
Portable Devices ◽  
Area Network ◽  
Single Chip ◽  
Single Node ◽  
Control Protocol ◽  
Control Terminal

With the development of household appliances, the short of communication among them is more and more becoming a problem. At present there is no central point of control among the traditional home appliances, and we cannot access them through Internet. To solve these issues, home network is proposed to connect all the appliances, home PC and portable devices together using network technology. Controlling all the appliances through one single node ( the home network gateway), home network makes life much simpler and convenient. There are several local area network technologies applicable to home network. Bluetooth technology is chosen in this paper as the home networking technology due to its many advantages over others. The implementation scheme of home control sub-network based on Bluetooth serial part profile ( SPP) and the standards of Home Network Platform in China is proposed. According to actual application fields, the communication protocol architecture for this scheme is established by using appliance control protocol promoted by the manufacturers and universal device control protocol ( UDCP) over SPP. Many management functions of appliance terminals are realized such as appending, login, operation, logout and alarming. Implementation methods of appliance terminal based on an entirely embedded single-chip manner and mobile control terminal which is realized by computer simulation are proposed. Analysis and solution of baud rate error brought by inaccurate crystal frequencies are presented. Further discussion about applying ad hoc technology to home control sub-network is carried out.

The Second Lebanon War Experience at Western Galilee Hospital

2015 ◽  
Vol 10 (1) ◽  
pp. 152-156
Author(s):  
Bartholomew Lino ◽  
Arie Eisenman ◽  
Richard Schuster ◽  
Carlos Giloni ◽  
Masad Bharoum ◽  
...  
Keyword(s):  
Stress Disorder ◽  
Acute Stress ◽  
Medical Center ◽  
Emergency Evacuation ◽  
Physical Injury ◽  
Conflict Zones ◽  
Major Medical Center ◽  
War Experience ◽  
Second Lebanon War ◽  
Rapid Evacuation

AbstractThe summer of 2006 in northern Israel served as the battleground for the second war against Hezbollah based along Israel’s border with southern Lebanon. Western Galilee Hospital (WGH), which is located only 6 miles from the Lebanese border, served as a major medical center in the vicinity of the fighting. The hospital was directly impacted by Hezbollah with a Katyusha rocket, which struck the ophthalmology department on the 4th floor. WGH was able to utilize a 450-bed underground facility that maintained full hospital functionality throughout the conflict. In a major feat of rapid evacuation, the entire hospital population was relocated under the cover of darkness to these bunkers in just over 1 hour, thus emptying the building prior to the missile impact. Over half of the patients presenting during the conflict did not incur physical injury but qualified as acute stress disorder patients. The particulars of this evacuation remain unique owing to the extraordinary circumstances, but many of the principles employed in this maneuver may serve as a template for other hospitals requiring emergency evacuation. Hospital functionality drastically changed to accommodate the operational reality of war, and many of these tactics warrant closer investigation for possible implementation in other conflict zones. (Disaster Med Public Health Preparedness. 2016;10:152–156)

scholarly journals BIM and Computer Vision-Based Framework for Fire Emergency Evacuation Considering Local Safety Performance

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3851
Author(s):  
Hui Deng ◽  
Zhibin Ou ◽  
Genjie Zhang ◽  
Yichuan Deng ◽  
Mao Tian
Keyword(s):  
Computer Vision ◽  
Fire Hazard ◽  
Route Planning ◽  
Emergency Evacuation ◽  
Automatic Generation ◽  
Indoor Navigation ◽  
Safety Performance ◽  
Information Modeling ◽  
Interior Space ◽  
Local Safety

Fire hazard in public buildings may result in serious casualties due to the difficulty of evacuation caused by intricate interior space and unpredictable development of fire situations. It is essential to provide safe and reliable indoor navigation for people trapped in the fire. Distinguished from the global shortest rescue route planning, a framework focusing on the local safety performance is proposed for emergency evacuation navigation. Sufficiently utilizing the information from Building Information Modeling (BIM), this framework automatically constructs geometry network model (GNM) through Industry Foundation Classes (IFC) and integrates computer vision for indoor positioning. Considering the available local egress time (ALET), a back propagation (BP) neural network is applied for adjusting the rescue route according to the fire situation, improving the local safety performance of evacuation. A campus building is taken as an example for proving the feasibility of the framework proposed. The result indicates that the rescue route generated by proposed framework is secure and reasonable. The proposed framework provides an idea for using real-time images only to implement the automatic generation of rescue route when a fire hazard occurs, which is passive, cheap, and convenient.

scholarly journals Design and testing of a dynamic reactive signage network towards fire emergency evacuations

2020 ◽  
Vol 10 (6) ◽  
pp. 5853
Author(s):  
Christopher S. Baidal ◽  
Nestor X. Arreaga ◽  
Vladimir Sanchez Padilla
Keyword(s):  
Computer Vision ◽  
Pilot Project ◽  
Emergency Evacuation ◽  
Dijkstra Algorithm ◽  
Emergency Evacuations ◽  
Integration Of Technology ◽  
Evacuation Routes ◽  
Evacuation Route ◽  
Design And Testing ◽  
Evacuation System

The loss of several lives happens in events of natural disasters, due to the strength of nature or the static evacuation routes that usually directs towards a unique exit pathway. This paper proposes the integration of technology tools such as servers and open-source sensors into a reactive signage network to provide an updated and dynamical emergency evacuation system focusing specifically on fire situations. This pilot project works using microcontrollers that capture and manages into a server the surrounding information, setting evacuation routes and behaving according to the Dijkstra algorithm allowing the identification of obstacles or possible incidents that occur spontaneously during an evacuation. This process sends updates to the server either the evacuation route keeps the same or if a modification is required based on the information provided by the sensors about different areas, warning the shortest path for evacuation using computer vision support.

scholarly journals Penerapan Algoritma Genetika dan Algoritma Ghost Framework pada Game Ms. Pacman

2019 ◽  
Vol 5 (3) ◽  
pp. 174
Author(s):  
Yongky Budi Setiawanda ◽  
Muhammad Khulqi Rasyid ◽  
Muhammad Jauharul Ramadhan ◽  
Anggit Dwi Hartanto
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithm ◽  
Control System ◽  
Management Actions ◽  
Ga Algorithm ◽  
Direction Of Movement ◽  
Control Terminal

Pacman merupakan salah satu game klasik yang terkenal pada dekade 80-an dan masih sampai sekarang menarik untuk menjadi objek penelitian tentang penerapan berbagai konsep Artificial Intellegent (AI). Tujuan utama dari game ini adalah, mendapatkan poin sebanyak-banyaknya sambil menghidar dari kejaran ghost dan mendapatkan poin tambahan saat memakan ghost setelah mendapatkan pil super. Pergerakan masing-masing ghost ditentukan oleh algoritma DFS dan BFS yang diterapkan pada Ghost Framework. Algoritma tersebut sering digunakan untuk membandingkan algoritma lain dalam hal efektifitas. Penulis memanfaatkan Algoritma DFS dan BFS pada ghost digame Pacman untuk membandingkan keefektifan Algoritma Genetika (GA). Penulis menerapkan Algoritma Genetika pada player Pacman sebagai pengganti control. Terminal akan bertugas untuk mengambil nilai semua kemungkinan arah gerakan di setiap waktu selama permainan. Berdasarkan nilai-nilai ini pengontrol dapat mengontrol MS. Pacman melawan Ghost framework. Dengan desain ini, Penulis mengurangi kompleksitas solusi GA dengan menghapus semua control tindakan tugas manajemen dari system. Setelah melakukan beberapa pengujian, Penulis mendapatkan hasil dimana GA menghasilkan rerata score 8,330 yang lebih tinggi dibandingkan dengan player amatir dan kontroler lain. Dari hasil yang tersedia, Penulis menyimpulkan bahwa kinerja GA sebagai controller MS. Pacman dapat dikatakan baik.Kata Kunci — Algoritma Genetika, Pacman, Ghost FrameworkPacman is one of the famous classic games in the 80s and is still interesting to be the object of research on Artificial Intelligence (AI). The main goal of this game is to get as many points as possible while avoiding ghost chases and get extra points when eating ghost after getting super pills. The movement of each ghost is determined by the DFS and BFS algorithms that are applied to Ghost Framework. The algorithm is often used to compare other algorithms in terms of effectiveness. Writer use the DFS and BFS Algorithm on ghost in the Pacman game to compare the effectiveness of the Genetic (GA) Algorithm. The terminal will take the value of all possible direction of movement during the game. Based on these values the controller can control MS. Pacman against Ghost framework. With this design, Writer reduce the complexity of the GA solution by removing all management actions from the control system. After doing some testing, Writer get results where GA produces a higher score compared to other amateur players and controllers. From available results, Writer conclude that the performance of GA as a MS. Pacman controller is good.Keywords — Genetic Algorithm, Pacman, Ghost Framework

scholarly journals Modeling and Simulation of Athlete’s Error Motion Recognition Based on Computer Vision

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Luo Dai
Keyword(s):  
Computer Vision ◽  
Action Recognition ◽  
Human Body ◽  
Template Matching ◽  
Human Error ◽  
Recognition Rate ◽  
Feature Reduction ◽  
Action Sequence ◽  
Motion Energy ◽  
Flow Information

Computer vision is widely used in manufacturing, sports, medical diagnosis, and other fields. In this article, a multifeature fusion error action expression method based on silhouette and optical flow information is proposed to overcome the shortcomings in the effectiveness of a single error action expression method based on the fusion of features for human body error action recognition. We analyse and discuss the human error action recognition method based on the idea of template matching to analyse the key issues that affect the overall expression of the error action sequences, and then, we propose a motion energy model based on the direct motion energy decomposition of the video clips of human error actions in the 3 Deron action sequence space through the filter group. The method can avoid preprocessing operations such as target localization and segmentation; then, we use MET features and combine with SVM to test the human body error database and compare the experimental results obtained by using different feature reduction and classification methods, and the results show that the method has the obvious comparative advantage in the recognition rate and is suitable for other dynamic scenes.

Mobile Robot Navigation Using Open Computer Vision with Fuzzy Controller

2008 ◽  
Vol 12 (4) ◽  
pp. 336-341
Author(s):  
Julirose Gonzales ◽  
◽  
Zahari Taha
Keyword(s):  
Computer Vision ◽  
Mobile Robot ◽  
Fuzzy Controller ◽  
Robot Navigation ◽  
Processing Technique ◽  
General Purpose ◽  
Global Environment ◽  
Image Processing Technique ◽  
Mobile Robot Navigation ◽  
Direction Of Movement

This research presents a fuzzy controller technique in navigation with obstacle avoidance for a general purpose mobile robot in a given global environment with image processing technique using Open Source Computer Vision (OpenCV) library on Visual C++. Fuzzy Logic is used to control the navigation of the robot towards the goal while avoiding obstacles along the way by changing its direction of movement. The positions of the mobile robot, obstacle and the destination are taken into consideration and an overhead camera (above the robot’s environment) is used to gather these necessary information. The images captured are processed using different techniques to get the desired positions and is directly integrated with the fuzzy controller making the algorithm more efficient compared to other vision-guided navigation techniques.

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